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Purpose: Insulin-like growth factor-1 (IGF-1) has been associated with both protective and detrimental effects on the development of ischemic heart disease. The relationship between IGF-1 levels and major adverse cardiovascular events (MACE) in acute coronary syndrome (ACS) patients remains unclear. This study aimed to investigate the relationship between IGF-1 admission levels in hyperglycemic ACS patients and: (1) MACE over a 5 years follow-up, (2) type 2 diabetes at discharge, and (3) post-ACS myocardial infarct size and dysfunction. Methods: This was a post hoc analysis of the BIOMArCS-2 randomized controlled trial. From July 2008 to February 2012, 276 ACS patients with admission plasma glucose level between 140 and 288 mg/dL were included. Records of the composite of all-cause mortality and recurrent non-fatal myocardial infarction were obtained during 5 years follow-up. Venous blood samples were collected on admission. IGF-1 was measured batchwise after study completion. Oral glucose tolerance test was performed to diagnose type 2 diabetes, whereas infarct size and left ventricular function were assessed by myocardial perfusion scintigraphy (MPS) imaging, 6 weeks post-ACS. Results: Cumulative incidence of MACE was 24% at 5 years follow-up. IGF-1 was not independently associated with MACE (HR:1.00 (95%CI:0.99-1.00), p = 0.29). Seventy-eight patients (28%) had type 2 diabetes at discharge, and the highest quartile of IGF-1 levels was associated with the lowest incidence of diabetes (HR:0.40 (95%CI:0.17-0.95), p = 0.037). IGF-1 levels were not associated with post-ACS myocardial infarct size and dysfunction. Conclusions: IGF-1 carries potential for predicting type 2 diabetes, rather than long-term cardiovascular outcomes and post-ACS myocardial infarct size and dysfunction, in hyperglycemic ACS patients. [ABSTRACT FROM AUTHOR]

Background Elevated plasma glucose levels on admission (APG) are very common in patients with acute coronary syndrome (ACS) and can be the first indication of diabetes mellitus. Objective To provide insight into the prevalence of previously undiagnosed diabetes and to compare different methods of diagnosing diabetes in patients with ACS. Methods Patients with ACS with elevated APG who participated in the BIOMArCS 2 glucose trial underwent an oral glucose tolerance test (OGTT) prior to discharge. 130 patients were included who underwent metabolic assessment. Of these, 109 had an OGTT and 13 patients had pre-existing diabetes. Results The OGTT results were categorised as (previously) undiagnosed diabetes in 35% of patients (fasting plasma glucose (FPG) ≥7.0 mmol/l or 2-h post-load glucose ≥11.1 mmol/l) and impaired glucose metabolism in 44% (FPG 6.1-6.9 mmol/l or post-load glucose 7.8-11.0 mmol/l), so only 21% had a normal glucose metabolism. Undiagnosed diabetes could not be adequately predicted with APG, FPG or HbA1c (area under the ROC curve 0.61, 0.75 and 0.72, respectively). Patients with abnormal glucose metabolism were significantly older, had higher admission HbA1c values, a higher Killip classification and more often had a prior stroke than patients with normal glucose metabolism. Conclusion 79% of hyperglycaemic patients with ACS were found to have abnormal glucose metabolism. As APG, HbA1c and FPG had a low sensitivity to detect undiagnosed diabetes, an OGTT appears to be the best test to assess the presence of previously undiagnosed diabetes or impaired glucose metabolism in hyperglycaemic patients with ACS. [ABSTRACT FROM AUTHOR]

Objective: Admission plasma glucose (APG) is a biomarker that predicts mortality in myocardial infarction (MI) patients. Therefore, APG may improve risk stratification based on the GRACE risk score. Methods: We collected data on baseline characteristics and long-term (median 55 months) outcome of 550 MI patients who entered our hospital in 2003 and 2006. We determined the GRACE risk score at admission for each patient, which was entered in a logistic regression model, together with APG, to evaluate their prognostic value for 6-month and 5-year mortality. Results: Patients with APG ≥7.8 mmol/l had a higher mortality than those with APG levels <7.8 mmol/l; 6 months: 13.7 versus 3.6%, p value <0.001; 5 years: 20.4 versus 11.1%, p value 0.003. After adjustment for the GRACE risk score variables, APG appeared a significant predictor of 6-month and 5-year mortality, adjusted OR 1.17 (1.06-1.29) and 1.12 (1.03-1.22). The combination of the GRACE risk score and APG increased the model's performance (discrimination C-index 0.87 vs. 0.85), although the difference was not significant (p = 0.095). Combining the GRACE risk score and APG reclassified 12.9% of the patients, but the net reclassification improvement was nonsignificant (p = 0.146). Conclusion: APG is a predictor of 6-month and 5-year mortality, each mmol/l increase in APG being associated with a mortality increase of 17 and 12%, respectively, independent of the GRACE risk score. However, adding APG to the GRACE model did not result in significantly improved clinical risk stratification. Copyright © 2012 S. Karger AG, Basel [ABSTRACT FROM AUTHOR]

Aims The applicability of currently available risk prediction models for patients undergoing percutaneous coronary interventions (PCIs) is limited. We aimed to develop a model for the prediction of in-hospital mortality after PCI that is based on contemporary and representative data from a European perspective. Methods and results Our analyses are based on the Euro Heart Survey of PCIs, which contains information on 46 064 consecutive patients who underwent PCI for different indications in 176 participating European centres during 2005–08. Patients were randomly divided into a training (n = 23 032) and a validation (n = 23 032) set with similar characteristics. In these sets, 339 (1.5%) and 305 (1.3%) patients died during hospitalization, respectively. On the basis of the training set, a logistic model was constructed that related 16 independent patient or lesion characteristics with mortality, including PCI indication, advanced age, haemodynamic instability, multivessel disease, and proximal LAD disease. In both the training and validation data sets, the model had a good performance in terms of discrimination (C-index 0.91 and 0.90, respectively) and calibration (Hosmer–Lemeshow P-value 0.39 and 0.18, respectively). Conclusion In-hospital mortality in PCI patients was well predicted by a risk score that contains 16 factors. The score has strong applicability for European practices. [ABSTRACT FROM PUBLISHER]